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All Journal Green Intelligent Systems and Applications
Woo, Pei-Jun
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Effectiveness of Using Artificial Intelligence for Early Child Development Screening Gau, Michael-Lian; Ting, Huong-Yong; Toh, Teck-Hock; Wong, Pui-Ying; Woo, Pei-Jun; Wo, Su-Woan; Tan, Gek-Ling
Green Intelligent Systems and Applications Volume 3 - Issue 1 - 2023
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v3i1.229

Abstract

This study presents a novel approach to recognizing emotions in infants using machine learning models. To address the lack of infant-specific datasets, a custom dataset of infants' faces was created by extracting images from the AffectNet dataset. The dataset was then used to train various machine learning models with different parameters. The best-performing model was evaluated on the City Infant Faces dataset. The proposed deep learning model achieved an accuracy of 94.63% in recognizing positive, negative, and neutral facial expressions. These results provide a benchmark for the performance of machine learning models in infant emotion recognition and suggest potential applications in developing emotion-sensitive technologies for infants. This study fills a gap in the literature on emotion recognition, which has largely focused on adults or children and highlights the importance of developing infant-specific datasets and evaluating different parameters to achieve accurate results.
Co-Authors Gau, Michael-Lian Tan, Gek-Ling Ting, Huong-Yong Toh, Teck-Hock Wo, Su-Woan Wong, Pui-Ying